T Perk

Repeatability of Quantitative 18F-NaF PET: A Multicenter Study

18F-NaF, a PET radiotracer of bone turnover, has shown potential as an imaging biomarker for assessing the response of bone metastases to therapy. This study aimed to evaluate the repeatability of 18F-NaF PET–derived SUV imaging metrics in individual bone lesions from patients in a multicenter study. Methods: Thirty-five castration-resistant prostate cancer patients with multiple metastases underwent 2 whole-body (test–retest) 18F-NaF PET/CT scans 3 ± 2 d apart from 1 of 3 imaging sites. A total of 411 bone lesions larger than 1.5 cm3 were automatically segmented using an SUV threshold of 15 g/mL. Two levels of analysis were performed: lesion-level, in which measures were extracted from individual-lesion regions of interest (ROI), and patient-level, in which all lesions within a patient were grouped into a patient ROI for analysis. Uptake was quantified with SUVmax, SUVmean, and SUVtotal. Test–retest repeatability was assessed using Bland–Altman analysis, intraclass correlation coefficient (ICC), coefficient of variation, critical percentage difference, and repeatability coefficient. The 95% limit of agreement (LOA) of the ratio between test and retest measurements was calculated. Results: At the lesion level, the coefficient of variation for SUVmax, SUVmean, and SUVtotal was 14.1%, 6.6%, and 25.5%, respectively. At the patient level, it was slightly smaller: 12.0%, 5.3%, and 18.5%, respectively. ICC was excellent (>0.95) for all SUV metrics. Lesion-level 95% LOA for SUVmax, SUVmean, and SUVtotal was (0.76, 1.32), (0.88, 1.14), and (0.63, 1.71), respectively. Patient-level 95% LOA was slightly narrower, at (0.79, 1.26), (0.89, 1.10), and (0.70, 1.44), respectively. We observed significant differences in the variance and sample mean of lesion-level and patient-level measurements between imaging sites. Conclusion: The repeatability of SUVmax, SUVmean, and SUVtotal for 18F-NaF PET/CT was similar between lesion- and patient-level ROIs. We found significant differences in lesion-level and patient-level distributions between sites. These results can be used to establish 18F-NaF PET–based criteria for assessing treatment response at the lesion and patient levels. 18F-NaF PET demonstrates repeatability levels useful for clinically quantifying the response of bone lesions to therapy.

Development and evaluation of an articulated registration algorithm for human skeleton registration

Accurate registration over multiple scans is necessary to assess treatment response of bone diseases (e.g. metastatic bone lesions). This study aimed to develop and evaluate an articulated registration algorithm for the whole-body skeleton registration in human patients. In articulated registration, whole-body skeletons are registered by auto-segmenting into individual bones using atlas-based segmentation, and then rigidly aligning them. Sixteen patients (weight = 80-117 kg, height = 168-191 cm) with advanced prostate cancer underwent the pre- and mid-treatment PET/CT scans over a course of cancer therapy. Skeletons were extracted from the CT images by thresholding (HU>150). Skeletons were registered using the articulated, rigid, and deformable registration algorithms to account for position and postural variability between scans. The inter-observers agreement in the atlas creation, the agreement between the manually and atlas-based segmented bones, and the registration performances of all three registration algorithms were all assessed using the Dice similarity index-DSIobserved, DSIatlas, and DSIregister. Hausdorff distance (dHausdorff) of the registered skeletons was also used for registration evaluation. Nearly negligible inter-observers variability was found in the bone atlases creation as the DSIobserver was 96 ± 2%. Atlas-based and manual segmented bones were in excellent agreement with DSIatlas of 90 ± 3%. Articulated (DSIregsiter = 75 ± 2%, dHausdorff = 0.37 ± 0.08 cm) and deformable registration algorithms (DSIregister = 77 ± 3%, dHausdorff = 0.34 ± 0.08 cm) considerably outperformed the rigid registration algorithm (DSIregsiter = 59 ± 9%, dHausdorff = 0.69 ± 0.20 cm) in the skeleton registration as the rigid registration algorithm failed to capture the skeleton flexibility in the joints. Despite superior skeleton registration performance, deformable registration algorithm failed to preserve the local rigidity of bones as over 60% of the skeletons were deformed. Articulated registration is superior to rigid and deformable registrations by capturing global flexibility while preserving local rigidity inherent in skeleton registration. Therefore, articulated registration can be employed to accurately register the whole-body human skeletons, and it enables the treatment response assessment of various bone diseases.

Quantitative Assessment of Early [18F]Sodium Fluoride Positron Emission Tomography/Computed Tomography Response to Treatment in Men With Metastatic Prostate Cancer to Bone

Purpose [18F]Sodium fluoride (NaF) positron emission tomography (PET)/computed tomography (CT) is a promising radiotracer for quantitative assessment of bone metastases. This study assesses changes in early NaF PET/CT response measures in metastatic prostate cancer for correlation to clinical outcomes. Patients and Methods Fifty-six patients with metastatic castration-resistant prostate cancer (mCRPC) with osseous metastases had NaF PET/CT scans performed at baseline and after three cycles of chemotherapy (n = 16) or androgen receptor pathway inhibitors (n = 40). A novel technology, Quantitative Total Bone Imaging, was used for analysis. Global imaging metrics, including maximum standardized uptake value (SUVmax) and total functional burden (SUVtotal), were extracted from composite lesion-level statistics for each patient and tracked throughout treatment. Progression-free survival (PFS) was calculated as a composite end point of progressive events using conventional imaging and/or physician discretion of clinical benefit; NaF imaging was not used for clinical evaluation. Cox proportional hazards regression analyses were conducted between imaging metrics and PFS. Results Functional burden (SUVtotal) assessed midtreatment was the strongest univariable PFS predictor (hazard ratio, 1.97; 95% CI, 1.44 to 2.71; P < .001). Classification of patients based on changes in functional burden showed stronger correlation to PFS than did the change in number of lesions. Various global imaging metrics outperformed baseline clinical markers in predicting outcome, including SUVtotal and SUVmean. No differences in imaging response or PFS correlates were found for different treatment cohorts. Conclusion Quantitative total bone imaging enables comprehensive disease quantification on NaF PET/CT imaging, showing strong correlation to clinical outcomes. Total functional burden assessed after three cycles of hormonal therapy or chemotherapy was predictive of PFS for men with mCRPC. This supports ongoing development of NaF PET/CT-based imaging biomarkers in mCRPC to bone.

Diagnostic classification of solitary pulmonary nodules using dual time 18 F-FDG PET/CT image texture features in granuloma-endemic regions

Lung cancer, the most commonly diagnosed cancer worldwide, usually presents as solid pulmonary nodules (SPNs) on early diagnostic images. Classification of malignant disease at this early timepoint is critical for improving the success of surgical resection and increasing 5-year survival rates. 18F-fluorodeoxyglucose (18F-FDG) PET/CT has demonstrated value for SPNs diagnosis with high sensitivity to detect malignant SPNs, but lower specificity in diagnosing malignant SPNs in populations with endemic infectious lung disease. This study aimed to determine whether quantitative heterogeneity derived from various texture features on dual time FDG PET/CT images (DTPI) can differentiate between malignant and benign SPNs in patients from granuloma-endemic regions. Machine learning methods were employed to find optimal discrimination between malignant and benign nodules. Machine learning models trained by texture features on DTPI images achieved significant improvements over standard clinical metrics and visual interpretation for discriminating benign from malignant SPNs, especially by texture features on delayed FDG PET/CT images.

WE‐FG‐202‐05: Quantification of Bone Flare On [F‐18] NaF PET/CT in Metastatic Prostate Cancer

PURPOSE Bone flare has been observed on Tc-99m bone scans during early assessment in metastatic Castration-Resistant Prostate Cancer (mCRPC) patients receiving select androgen-signaling pathway (AR) targeted treatments, including CYP17-inhibitor Abiraterone. This study investigates the appearance and potential clinical impact of bone flare in mCRPC patients receiving CYP17-inhibitors using 18 F-NaF PET/CT. METHODS Twenty-three mCRPC patients being treated with CYP17-inhibitors received NaF PET/CT scans at baseline, week 6, and week 12 of treatment. Individual lesions were identified using a SUV>15 threshold within skeletal regions and articulated bone registration was used to track lesions between scans. Standard SUV metrics were extracted globally for each patient (pSUV) and for each individual lesion (iSUV). Differences in metrics across time-points were compared using Wilcoxon signed-rank tests. Cox proportional hazard regression analyses were conducted between global metrics and progression-free survival (PFS). RESULTS Nineteen patients (83%) showed increasing NaF PET global metrics at week 6, with pSUVtotal reflecting consensus change across other global metrics with median increase +33% (range +2 to 205%). Of these patients, 14 showed subsequent decrease in pSUVtotal , with a median of -17% (range -76 to -1%), indicating flare phenomenon. Increasing pSUVmean at week 6 correlated with extended clinical PFS (HR = 0.58, p=0.02). New lesions did not account for the initial increase in global NaF metrics. Lesion-level analysis reveals 316 lesions in the 14 patients exhibiting global flare. On average, 75% (sd: 22%) of lesions follow global trends with iSUVtotal increasing at week 6 and 65% (sd: 17%) showing iSUVtotal decrease at week 12. CONCLUSION Bone flare was detected on NaF PET/CT in the first 6 weeks of treatment for mCRPC patients receiving CYP17-inhibitors, subsiding by week 12. Characterization provided in this study suggests prolonged PFS in patients showing bone flare early in select AR-directed treatments. Prostate Cancer Foundation.

TU‐AB‐BRA‐05: Repeatability of [F‐18]‐NaF PET Imaging Biomarkers for Bone Lesions: A Multicenter Study

Purpose: Quantifying the repeatability of imaging biomarkers is critical for assessing therapeutic response. While therapeutic efficacy has been traditionally quantified by SUV metrics, imaging texture features have shown potential for use as quantitative biomarkers. In this study we evaluated the repeatability of quantitative 18F-NaF PET-derived SUV metrics and texture features in bone lesions from patients in a multicenter study. Methods: Twenty-nine metastatic castrate-resistant prostate cancer patients received whole-body test-retest NaF PET/CT scans from one of three harmonized imaging centers. Bone lesions of volume greater than 1.5 cm3 were identified and automatically segmented using a SUV>15 threshold. From each lesion, 55 NaF PET-derived texture features (including first-order, co-occurrence, grey-level run-length, neighbor gray-level, and neighbor gray-tone difference matrix) were extracted. The test-retest repeatability of each SUV metric and texture feature was assessed with Bland-Altman analysis. Results: A total of 315 bone lesions were evaluated. Of the traditional SUV metrics, the repeatability coefficient (RC) was 12.6 SUV for SUVmax, 2.5 SUV for SUVmean, and 4.3 cm3 for volume. Their respective intralesion coefficients of variation (COVs) were 12%, 17%, and 6%. Of the texture features, COV was lowest for entropy (0.03%) and highest for kurtosis (105%). Lesion intraclass correlation coefficient (ICC) was lowest for maximum correlation coefficient (ICC=0.848), and highest for entropy (ICC=0.985). Across imaging centers, repeatability of texture features and SUV varied. For example, across imaging centers, COV for SUVmax ranged between 11–23%. Conclusion: Many NaF PET-derived SUV metrics and texture features for bone lesions demonstrated high repeatability, such as SUVmax, entropy, and volume. Several imaging texture features demonstrated poor repeatability, such as SUVtotal and SUVstd. These results can be used to establish response criteria for NaF PET-based treatment response assessment. Prostate Cancer Foundation (PCF)

A statistically optimized regional thresholding method (SORT) for bone lesion detection in 18 F-NaF PET/CT imaging

Identification of individual lesions on 18F-NaF PET bone scans is a time-consuming and often subjective process that makes accurate characterization of disease burden challenging. Current automated methods either underestimate disease or struggle with high false positive rates. We developed a statistically optimized regional thresholding (SORT) method that optimizes detection of bone lesions. This study assessed 18F-NaF PET/CT scans of 37 bone metastatic prostate cancer patients. Each PET image was divided into 19 skeletal regions. Areas of disease in each skeletal region were identified by an experienced nuclear medicine physician. A region of interest (ROI) was placed at each disease location and local maxima were extracted for both healthy and diseased ROIs. Secondary physician review was performed after identification of suspicious local maxima. Region-specific SUV thresholds were determined based on receiver operating characteristic (ROC) analysis optimized for detection of malignant disease. The detection performance of the SORT thresholds were compared to commonly used SUV  >  10 g ml-1 (SUV10) and SUV  >  15 g ml-1 (SUV15) global thresholds. The sensitivity of the SORT thresholds to various factors was evaluated, such as the number of subjects evaluated or image reconstruction settings. 1751 lesions were manually identified by the nuclear medicine physician. SORT identified different thresholds in each skeletal region (SUV range: 3-13 g ml-1). Region-specific SORT thresholding resulted in higher sensitivity (95.8%) than commonly used global thresholds (82.8% for SUV10 and 58.4% for SUV15) while maintaining a high specificity (97.1%, compared to 97.3% for SUV10 and 100.0% for SUV15). Factors, such as reconstruction settings, had minimal impact on threshold optimization, resulting in an average change of 10% (range: 2%-17%) in thresholds for each factor. Region-specific SUV thresholding of NaF PET images for bone lesion detection in metastatic prostate patients was found to be superior to current global thresholding methods.

WE-H-207A-04: Impact of Lesion Location On the Repeatability of 18F-NaF PET/CT

PURPOSE Quantifying the repeatability of imaging biomarkers is critical for assessing therapeutic response. While 18 F-NaF PET/CT has shown to be a repeatable imaging method, research has not shown which factors may influence its repeatability. The purpose of this study was to evaluate whether the location of the lesion impacts the repeatability of quantitative 18 F-NaF PET-derived SUV metrics. METHODS Metastatic castrate-resistant prostate cancer patients with multiple bone lesions received whole-body test-retest NaF PET/CT scans. Malignant bone lesions of PET-defined volume greater than 1.5 cm3 were identified by a nuclear medicine physician and automatically delineated using a SUV>15 threshold. The maximum (SUVmax), average (SUVmean), and total (SUVtotal) SUV were extracted from each lesion. Atlas-based segmentation was used to divide each patient skeleton into 25 skeletal regions. Test-retest repeatability of each SUV metric was assessed with coefficient of variation (CV). RESULTS A total of 265 malignant bone lesions from 18 patients were identified by nuclear medicine physician. The largest proportion of bone lesions were localized to the spine (41%), with 41% of those lesions localized to the thoracic spine. One-way ANOVA showed that measurement differences differed significantly for all three metrics across locations (p<0.01 for each metrics). Overall, CV was smallest for SUVmean at 5.3%, followed by SUVmax at 11.5% and SUVtotal at 20.4%. Lesions in the pubis were consistently the most repeatable (CV(SUVmax)= 5.6%, CV(SUVmean)= 0.6%, CV(SUVtotal)= 2.9%). According to SUVmean, repeatability was poorest in the cervical spine (CV = 6.2%), whereas according to SUVmax and SUVtotal, repeatability was poorest in the ribs (CV(SUVmax)= 15.0%, CV(SUVtotal)= 29.8%). CONCLUSION Location of the lesion affects the repeatability of 18 F-NaF PET/CT, with the ribs and cervical spine having the lowest repeatability and the pubis having the highest repeatability. These results can be used to establish location-specific response criteria for NaF PET-based treatment response assessment.

MO‐AB‐BRA‐05: [18F]NaF PET/CT Imaging Biomarkers in Metastatic Prostate Cancer

PURPOSE Clinical use of 18 F-Sodium Fluoride (NaF) PET/CT in metastatic settings often lacks technology to quantitatively measure full disease dynamics due to high tumor burden. This study assesses radiomics-based extraction of NaF PET/CT measures, including global metrics of overall burden and local metrics of disease heterogeneity, in metastatic prostate cancer for correlation to clinical outcomes. METHODS Fifty-six metastatic Castrate-Resistant Prostate Cancer (mCRPC) patients had NaF PET/CT scans performed at baseline and three cycles into chemotherapy (N=16) or androgen-receptor (AR) inhibitors (N=39). A novel technology, Quantitative Total Bone Imaging (QTBI), was used for analysis. Employing hybrid PET/CT segmentation and articulated skeletal-registration, QTBI allows for response assessment of individual lesions. Various SUV metrics were extracted from each lesion (iSUV). Global metrics were extracted from composite lesion-level statistics for each patient (pSUV). Proportion of detected lesions and those with significant response (%-increase or %-decrease) was calculated for each patient based on test-retest limits for iSUV metrics. Cox proportional hazard regression analyses were conducted between imaging metrics and progression-free survival (PFS). RESULTS Functional burden (pSUVtotal ) assessed mid-treatment was the strongest univariate predictor of PFS (HR=2.03; p<0.0001). Various global metrics outperformed baseline clinical markers, including fraction of skeletal burden, mean uptake (pSUVmean ), and heterogeneity of average lesion uptake (pSUVhetero ). Of 43 patients with paired baseline/mid-treatment imaging, 40 showed heterogeneity in lesion-level response, containing populations of lesions with both increasing/decreasing metrics. Proportion of lesions with significantly increasing iSUVmean was highly predictive of clinical PFS (HR=2.0; p=0.0002). Patients exhibiting higher proportion of lesions with decreasing iSUVtotal saw prolonged radiographic PFS (HR=0.51; p=0.02). CONCLUSION Technology presented here provides comprehensive disease quantification on NaF PET/CT imaging, showing strong correlation to clinical outcomes. Total functional burden as well as proportions of similarly responding lesions was predictive of PFS. This supports ongoing development of NaF PET/CT based imaging biomarkers in mCRPC. Prostate Cancer Foundation.

SU-F-J-06: Optimized Patient Inclusion for NaF PET Response-Based Biopsies

PURPOSE A method to guide mid-treatment biopsies using quantitative [F-18]NaF PET/CT response is being investigated in a clinical trial. This study aims to develop methodology to identify patients amenable to mid-treatment biopsy based on pre-treatment imaging characteristics. METHODS 35 metastatic prostate cancer patients had NaF PET/CT scans taken prior to the start of treatment and 9-12 weeks into treatment. For mid-treatment biopsy targeting, lesions must be at least 1.5 cm3 and located in a clinically feasible region (lumbar/sacral spine, pelvis, humerus, or femur). Three methods were developed based on number of lesions present prior to treatment: a feasibility-restricted method, a location-restricted method, and an unrestricted method. The feasibility restricted method only utilizes information from lesions meeting biopsy requirements in the pre-treatment scan. The unrestricted method accounts for all lesions present in the pre-treatment scan. For each method, optimized classification cutoffs for candidate patients were determined. RESULTS 13 of the 35 patients had enough lesions at the mid-treatment for biopsy candidacy. Of 1749 lesions identified in all 35 patients at mid-treatment, only 9.8% were amenable to biopsy. Optimizing the feasibility-restricted method required 4 lesions at pre-treatment meeting volume and region requirements for biopsy, resulting patient identification sensitivity of 0.8 and specificity of 0.7. Of 6 false positive patients, only one patient lacked lesions for biopsy. Restricting for location alone showed poor results (sensitivity 0.2 and specificity 0.3). The optimized unrestricted method required patients have at least 37 lesions in pretreatment scan, resulting in a sensitivity of 0.8 and specificity of 0.8. There were 5 false positives, only one lacked lesions for biopsy. CONCLUSION Incorporating the overall pre-treatment number of NaF PET/CT identified lesions provided best prediction for identifying candidate patients for mid-treatment biopsy. This study provides validity for prediction-based inclusion criteria that can be extended to various clinical trial scenarios. Funded by Prostate Cancer Foundation.